An evolutionary compensatory negotiation model for distributed dynamic scheduling

Although a considerable amount of efforts has been devoted to developing optimum negotiation for dynamic scheduling, most of them are inappropriate for the non-cooperative, self-interested participants in a distributed project for practical purpose. In this paper, an agent-based approach with a mutual influencing, many-issue, one-to-many-party, compensatory negotiation model is proposed. In the model, the activity agents possess various negotiation tactics and strategies formed by respective self-interested owner's subjective preference, aim to find the contracts of schedule adjustment mutually acceptable to respective participant's acquaintance while encountering conflicts over rescheduling settlement. In order to find the fitting negotiation strategies that are optimally adapted for each activity agent, an evolutionary computation approach that encodes the parameters of tactics and strategies of an agent as genes in GAs is also addressed. In the final, a prototype with a case discussed in researches is evaluated to validate the feasibility and applicability of the model, and some characteristics and future works are also exhibited.